Plotly

Plotly is a powerful Python library for creating interactive plots. By default, Plotly displays information about data points when you hover over them. While this is useful in many cases, sometimes you might want to disable this hover behavior for specific traces or even the entire plot. See how to achieve this.

Controlling the range of the y-axis in Plotly is essential for effectively visualizing your data. This is how to set the y-axis range for various plot types in Plotly.

The legend in Plotly provides information about the traces in your plot. While often useful, there are situations where you might want to hide the legend. Check several ways to hide the legend in Plotly.

Plotly offers a wide range of options for customizing the appearance of your plots, including the color of lines. This is how to change line color in Plotly for various types of plots.

Plotly is a versatile Python library for creating interactive data visualizations. One of the most commonly used visualization types is the scatter plot, which allows you to visualize the relationship between two numerical variables. We’ll explore how to create interactive scatter plots using Plotly in Python, enabling you to explore and analyze your data with Continue reading

Plotly is a powerful Python library for creating visually appealing and interactive data visualizations. Histograms are a fundamental type of visualization used to represent the distribution of data. This tutorial will guide you through creating interactive histograms with Plotly, enabling you to effectively explore and understand your data’s distribution. Understanding Histograms A histogram is a Continue reading

Before beginning the creation of bar charts, verify that the Plotly library is installed in your Python environment. This can be accomplished by running pip install plotly in your terminal or command prompt, thereby enabling access to advanced visualization capabilities.

When working with Plotly, a “trace” is a fundamental component that represents a set of data points and how they should be displayed on a chart. We’ll explore how to add traces to Plotly charts in Python, enabling you to create complex and interactive visualizations.

Plotly offers extensive customization options for your plots, including adjusting the title font size. This guide demonstrates two methods to achieve this: using the layout argument and the update_layout method.

One of the features of Plotly is that it allows you to customize the appearance of your charts, including the title. We will show you how to create a title with multiple lines in Plotly, using different methods and options.

In Plotly, you can center the title of a plot by setting the title.x attribute to 0.5 and the title.xref attribute to “paper”. Here’s an example of how you can center the title of a plot in Plotly:

In Plotly, you can add a vertical line to a plot by using the “shape” attribute in the layout. Here’s a simple example in Python: